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Details of Grant 

EPSRC Reference: EP/S005021/1
Title: Prosperity Partnership in Quantum Software for Modeling and Simulation
Principal Investigator: Severini, Professor S
Other Investigators:
Green, Professor AG Browne, Professor D Linden, Professor N
Montanaro, Dr A Cubitt, Dr T Morton, Professor JJL
Researcher Co-Investigators:
Project Partners:
Google GTN Ltd National Physical Laboratory
PhaseCraft Ltd.
Department: Computer Science
Organisation: UCL
Scheme: Standard Research
Starts: 01 October 2018 Ends: 30 September 2023 Value (£): 1,902,859
EPSRC Research Topic Classifications:
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
24 Jul 2018 Prosperity Partnerships Interview Panel Announced
14 Jun 2018 Prosperity Partnerships Prioritisation Panel 2 - June 2018 Announced
Summary on Grant Application Form
Nature, at it deepest level, is notoriously difficult to model, as quantum mechanical effects cause the size of the problems to grow exponentially. This poses major challenges in the accurate simulation of molecules and crystals, thus limiting the power of computers to drive major advances in the development of new materials (from batteries and solar cells to superconductors), new chemical processes (designing better catalysts) and new drugs (engineering molecules for desired biological and pharmacological effects). Each of these challenges can be addressed through tools we will help establish in this Prosperity Partnership.

As Feyman observed, the best (and indeed only) way to accurately compute the behaviour of such quantum mechanical systems is to build a computer whose inner workings are fundamentally based on those same quantum mechanical principles. Such so-called 'quantum computers' require radically new hardware able to represent and maintain information in exotic quantum states involving superposition (where quantum bits can be 0 and 1) and entanglement. Major advances are being made world-wide using a variety of hardware platforms, and amongst the leading quantum processors today are those being developed at Google, based on superconducting circuits. In 2018, Google expects to announce a processor with 49 high-quality quantum bits - although this number may seem small compared to the billions of transistors in conventional processor chips, this 49-qubit processor will, we expect, demonstrate the ability to solve a computational problem beyond the capabilities of our most capable supercomputers. This first demonstration of quantum 'advantage' using a quantum processor chip, opens the door for a new research approach looking to characterise and harness the the capabilities of this new hardware and develop applications in the simulation and modeling of materials and molecules.

The Partnership brings together the University of Bristol and UCL and their research groups with long-standing expertise in the theory of quantum computing and simulation, and Google, a world leader in the design and development of advanced quantum computing hardware based on superconducting qubits. Our goal is to develop new and improved algorithms, verification techniques and benchmarks for simulation of quantum systems on near-term quantum computers, which we will implement and demonstrate on Google's hardware. Such an industrial-academic collaboration would have been impossible a few years ago; now working together in this way is essential to efficiently address the main challenges in this area, as our ability to able to run and test problems on real quantum hardware will have a dramatic effect on the pace of quantum application development. In addition, the Partnership includes two UK startups developing quantum software and "quantum-inspired" software sphere, playing a strong role in the development of commercial applications of the results of this project. Through the Partnership, we will therefore build the foundation of a quantum software industry in the UK, with a specific focus on quantum simulation.

Our programme is organised around a set of four main Challenges:

- How can we optimise quantum simulation algorithms for imperfect quantum computers?

- How do we test the behaviour of a quantum machine if it is classically un-simulatable?

- What are the potential applications of quantum simulations in the medium term?

- Can we quantify the computational complexity of problems and use this to improve algorithms?

Each of these raises issues that are both fundamental and practical: the former involving the development of tools that can reframe these questions in a quantifiable way and the latter in in the formulation of explicit practical tests that can be implemented on current devices. In addressing these questions, we aim to develop a firm basis for the development of quantum software well-adapted to current architectures
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